The present invention generally relates to communication systems, and more particularly, a code division multiple access (CDMA) communication. system. The invention provides an efficient method and apparatus for decoding data symbols in a receiver portion of a CDMA communication system.
Communications in a CDMA system involve coding and decoding data symbols at different stages. Data symbols, for transmission to a destination user, are encoded in a transmitter portion of the CDMA system before being transmitted over a communication link, such as a wireless link. Upon receiving the transmitted signal, the destination user decodes the data symbols to retrieve the information. A convolutional code is a very popular code used for the encoding operation. To achieve an effective communication between users, in addition to coding, data symbols are interleaved. A destination user in the process of receiving the information decodes and de-interleaves the received data symbols to retrieve the information. The combination of interleaving and convolutional coding provides a more effective way of dealing with channel disturbances, for example, due to noise, fading or interference from other users in a communication system, such as a CDMA system.
A combination of coding and interleaving commonly known as a turbo code performed in a transmitter of a CDMA communication system has shown to provide superior results in ways of dealing with channel disturbances. A combination of coding and interleaving commonly known as a Serial-Concatenated Code (SCC) has shown also to provide superior results. As such, a CDMA system may use either a turbo code or an SCC.
Generally speaking, a turbo code and a serial-concatenated code each include at least two encoding blocks. As such, a receiver attempting to decode the received data symbols may have to deal with two decoding operations. Multiple decoding operations in a receiver takes time and adds complexity and cost to the receiver portion of the CDMA systems.
Several differences exist between turbo and serial-concatenated codes. A turbo code uses parallel encoding, in contrast to a serial encoding used in serial-concatenated code. Such a difference presents a difficulty for a receiver attempting to provide decoding functionality for both turbo and serial-concatenated codes.
Therefore, there is a need for a method and apparatus with minimal complexity for fast and efficient decoding of encoded data symbols in a receiver.
According to various embodiments of the invention, a method and apparatus for decoding a data symbol Xi of a plurality of data symbols Xi, with subscript (i) having a value from (1) to (k), (k) being a finite number, includes determining initially a data symbol estimate for a number of data symbols of the plurality of data symbols Xi. A data symbol estimate is determined for a number of data symbols of a plurality of data symbols Yi. The plurality of data symbols Yi are produced in a transmitter in the communication system by encoding the plurality of data symbols Xi according to a first convolutional code. A data symbol estimate is determined for a number of data symbols of a plurality of data symbols Wi. The plurality of data symbols Wi are produced in the transmitter by interleaving, in case of serial-concatenated code, the plurality of data symbols Yi and Xi, and in case of turbo code, the plurality of data symbols Xi, to produce a plurality of data symbols Zi. The plurality of data symbols Zi are encoded according to a second convolutional code to produce the plurality of data symbols Wi. The estimates of data symbols Xi and Yi pass to a first decision node. The estimates of data symbols Xi and Yi passing to the first decision node include the estimates for the variables in an equation F1(Xi, Yi). The variables Xi and Yi in the equation F1 are determined according to the first convolutional code. The estimates of data symbols Wi and Zi pass to a second decision node. The estimates of data symbols Wi and Zi passing to the second decision node include the estimates for the variables in an equation F2(Wi, Zi). The variables Wi and Zi in the equation F2 are determined according to the second convolutional code. The estimates for the variables Zi include the estimates of data symbols Xi, or Yi, or Xi and Yi determined according to the interleaving. While equating the equations F1 and F2 to zero at respectively the first and second decision nodes, a new estimate is determined for each occurrence of the data symbol Xi at the first and second decision nodes. A new estimate for the data symbol Xi is determined based on the estimate determined at the initial step and the new estimate for each occurrence of the data symbol Xi at the first and second decision nodes.
The new estimate for the data symbol Xi may confidently hold a true value for the data symbol Xi. The process may be repeated many times until the new estimate for the data symbol Xi confidently holds a true value for the data symbol Xi. When more than one iteration is necessary to build the confidence level, an embodiment of the invention includes determining a normalized estimate of data symbol Xi based on the estimate determined at the initial step and at least one of the new estimates for each occurrence of the data symbol Xi at the first and second decision nodes. The steps of passing estimates of data symbols to the first and second nodes are repeated while substituting the normalized estimate of data symbol Xi for at least one of the estimates of data symbols Xi. As such, an embodiment of the invention provides a method and apparatus for determining at the same time in a parallel fashion estimates of the plurality of data symbols Xi with minimal delay and complexity.